CloudCrowd - NT/e Presentation on Scalable Cloud Transaction & ORM

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Matthew Fowler, NT/e
CloudSave
CloudTran
Scalable Transactions in the Cloud

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?
And the answer is
platform for mainstream Java developers
to use IMDG
for scalable, commercial applications
without worry and minimal hassle
for commercial advantage
It's a lump of middleware
built on, adding value to GigaSpaces

3
2001
WebLogic/J2EE specialisation
One week training course
4-point architecture for dummies
Messed-up architecture
revenue down
Automating server-side applications
J2EE/EJB
Spring/Hibernate

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3-5...5-10...10-20...1,000,000
Tracy's story: the path of successful apps
Database
Caching
In-memory Data Grid
The 50,000 club
Application scale drivers
Mobile phone growth, iPhone Apps
Micropayments
e-commerce continued growth

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Get an edge with performance
“Latency really matters ... 100ms of latency costs 1% in sales.” Amazon
“An extra 0.5 seconds in search page generation time dropped traffic by 20%.” Google
Please wait
.....................
“... almost half of visitors will abandon a site if they perceive a page or feature takes longer than 2 seconds to load. ” GetElastic

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6.5m, x10yrs, $400bn/yr
Mainstream Java developers
6.5m
most have 5-10 years experience
50 million man-years experience
Plain old application development market
$400bn/year
Can they build an IMDG application?
How can IMDG go mainstream?

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Explaining it to your Mom / Boss
IMDG - SOR
Persistent Storage

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Explaining it to a techie
System of Record in IMDG. Keep DB for
warehouse apps/BI
sleeping at night.
Catching the money:
ACID transactions
throughput, scalability, bullet-proof reliability
distributed, data + messaging
ORM - Object references, not foreign keys.Easy to program. Entity groups for performance.

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In-Memory Data Bases - Are You Crazy?
What's it worth:
Loss of sales, traffic - 5% vulnerable, saved by speed of IMDG
For $100m/year co:
$5m/year revenue for good behaviour
Customer/order/product data - 2million * 16Kb
8 servers in grid for 32GB live data
8 servers isn't a lot
Worth doing the numbers!

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Distributed Transactions
Low Reliability
Complicated Programming
of Unknowing
Unintended Consequences
Fear and loathing ...

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, 1, 2, 3, ... 
Other alternatives
forget transactions, forget databases
Dan's the Man
GoogleApps on V2 last we heard

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How is it possible?
Distributed Cloud Transactions
Redefining the problem
Grid connected
Helland's get out clause
System of Record is in the grid
No voting - 1PC not 2PC
Commit to backed-up memory
Leverage the GigaSpaces platform
SBA/Entity Groups, Transactions, SQL Queries, Backups

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200/ ... 2,000 ... 20,000/second

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Transactions you can count on

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Transactions you can count on

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Herding Cats - Java Style
How to distribute data
How to find it
How to resolve references
IMDG versus user view: FK ↔ OO
Atomicity on failure
Timeouts
Scalability
Consistency and isolation

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The 'T' Word
GigaSpaces Local Transactions
GigaSpaces Distributed Transactions
Mirror service
see Cat-Herding 101

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How CloudTran ORM works
Partitioning
(entity groups)
Client
Gridsearch
OL
Order
Service
Commit
Data
Data
TxB
Commit
Commit
Confirm
Confirm
Tx
Messaging
Datasources

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300 .. 700 .. 900 .. 2,100
Performance of transaction buffer
Tiny Transactions per second

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Virgin Airways
LastMinute.com
IMDG
In-Cloud Federated Applications
IMDG
CloudTran -FederatedTransaction Buffer

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Scalable transactions in the cloud?
platform for mainstream Java developers
to use IMDG
for scalable, commercial applications
without worry and minimal hassle
for commercial advantage
GigaSpaces
CloudTran

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End

CloudCrowd - NT/e Presentation on Scalable Cloud Transaction & ORM

by Nati Shalom on Dec 09, 2009

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CloudCrowd - NT/e Presentation on Scalable Cloud Transaction & ORM — Presentation Transcript

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